167 lines
4.9 KiB
Markdown
167 lines
4.9 KiB
Markdown
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# Documentation
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- Class name: ImageEffectsAdjustment
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- Category: image/effects
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- Output node: False
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ImageEffectsAdjustment节点对一批图像应用一系列图像调整，包括亮度、对比度、饱和度、色相、伽马值和锐度，以及RGB颜色缩放。它允许对图像的视觉方面进行微调，以实现所需的效果或修正。
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# Input types
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## Required
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- images
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- 需要调整的图像批次。每项调整都会应用于批次中的所有图像，从而实现对多个输入的一致图像处理。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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- brightness
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- 调整图像的亮度水平。大于1.0的值会增加亮度，而小于1.0的值会降低亮度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- contrast
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- 修改图像的对比度。大于1.0的值会增强对比度，而小于1.0的值会降低对比度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- saturation
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- 改变图像的饱和度水平，增强或减弱颜色的强度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- hue
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- 改变图像的色相，允许在色谱上进行偏移。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- gamma
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- 对图像应用伽马校正，调整亮度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- sharpness
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- 调整图像的锐度，使其看起来更清晰或更柔和。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- red
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- 缩放图像的红色通道，影响红色色调的强度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- green
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- 缩放图像的绿色通道，影响绿色色调的强度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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- blue
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- 缩放图像的蓝色通道，影响蓝色色调的强度。
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- Comfy dtype: FLOAT
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- Python dtype: float
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# Output types
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- image
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- 应用指定调整后的图像批次，可能包括亮度、对比度、饱和度、色相、伽马值、锐度和RGB颜色缩放的变化。
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- Comfy dtype: IMAGE
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- Python dtype: torch.Tensor
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## Usage tips
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- Infra type: `GPU`
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- Common nodes: unknown
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## Source code
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```python
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class ImageEffectsAdjustment:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"images": ("IMAGE",),
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"brightness": ("FLOAT", {
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"default": 1.0,
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"step": 0.01
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}),
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"contrast": ("FLOAT", {
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"default": 1.0,
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"step": 0.01
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}),
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"saturation": ("FLOAT", {
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"default": 1.0,
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"step": 0.01
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}),
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"hue": ("FLOAT", {
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"default": 0.5,
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"max": 1.0,
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"step": 0.01
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}),
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"gamma": ("FLOAT", {
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"default": 1.0,
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"step": 0.01
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}),
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"sharpness": ("FLOAT", {
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"default": 1.0,
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"step": 0.01
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}),
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"red": ("FLOAT", {
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"default": 1.0,
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"step": 0.01
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}),
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"green": ("FLOAT", {
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"default": 1.0,
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"step": 0.01
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}),
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"blue": ("FLOAT", {
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"default": 1.0,
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"step": 0.01
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}),
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},
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "node"
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CATEGORY = "image/effects"
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def node(self, images, brightness, contrast, saturation, hue, gamma, sharpness, red, green, blue):
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# noinspection PyUnboundLocalVariable
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def apply(img):
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rgba = False
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if len(img[0, 0, :]) == 4:
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a = img[:, :, 3].unsqueeze(2)
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img = img[:, :, 0:3]
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rgba = True
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img = img.permute(2, 0, 1)
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if brightness != 1.0:
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img = F.adjust_brightness(img, brightness)
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if contrast != 1.0:
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img = F.adjust_contrast(img, contrast)
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if saturation != 1.0:
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img = F.adjust_saturation(img, saturation)
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if hue != 0.5:
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img = F.adjust_hue(img, hue - 0.5)
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if gamma != 1.0:
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img = F.adjust_gamma(img, gamma)
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if sharpness != 1.0:
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img = F.adjust_sharpness(img, sharpness)
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img = img.permute(1, 2, 0)
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r, g, b = torch.chunk(img, 3, dim=2)
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r = torch.clamp(r * red, 0, 1)
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g = torch.clamp(g * green, 0, 1)
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b = torch.clamp(b * blue, 0, 1)
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if rgba:
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return torch.cat([r, g, b, a], dim=2)
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else:
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return torch.cat([r, g, b], dim=2)
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return (torch.stack([
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apply(images[i]) for i in range(len(images))
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]),)
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```
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